Measuring regional energy efficiencies in China: a meta-frontier SBM-Undesirable approach

Under the framework of meta-frontier, we employ the slacks-based measurement (SBM)-Undesirable approach to explore China’s provincial energy efficiencies and meta-technology ratios (MTRs) of eight major economic regions during 2000–2014. The results obtained show that: firstly, the SBM-Undesirable model involving a undesirable output of CO2 emission is more reasonable than the SBM model for measuring China’s provincial energy efficiencies. Secondly, there are severe imbalances of energy efficiencies between regions due to their imbalanced energy technologies. Thirdly, energy efficiencies of the southern, eastern and northern coastal regions are high with advanced energy technologies. Energy technology gaps between regional and meta-technologies of southwest, eastern coastal and northern coastal regions are shrinking; however, the ones of remaining regions are widening. Fourthly, energy technology of overall China has a U-shaped trend; however, the ones of provinces in each region are characterized as a club convergence.

[1]  Ning Zhang,et al.  Energy efficiency, CO2 emission performance and technology gaps in fossil fuel electricity generation in Korea: A meta-frontier non-radial directional distance functionanalysis , 2013 .

[2]  B. W. Ang,et al.  Slacks-based efficiency measures for modeling environmental performance , 2006 .

[3]  Kaoru Tone,et al.  A slacks-based measure of efficiency in data envelopment analysis , 1997, Eur. J. Oper. Res..

[4]  Jin-Li Hu,et al.  Total-factor energy efficiency of regions in China , 2006 .

[5]  Yue-Jun Zhang,et al.  The allocation of carbon emission intensity reduction target by 2020 among provinces in China , 2015, Natural Hazards.

[6]  W. Cooper,et al.  Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software , 1999 .

[7]  Yue‐Jun Zhang,et al.  The evaluation of environmental capacity: evidence in Hunan province of China , 2016 .

[8]  Peng Zhou,et al.  A survey of data envelopment analysis in energy and environmental studies , 2008, Eur. J. Oper. Res..

[9]  Yue‐Jun Zhang,et al.  Direct energy rebound effect for road passenger transport in China: A dynamic panel quantile regression approach , 2015 .

[10]  Jin-Li Hu,et al.  Renewable energy and macroeconomic efficiency of OECD and non-OECD economies , 2007 .

[11]  G. Battese,et al.  A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies , 2004 .

[12]  Cláudia S. Sarrico,et al.  Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software , 2001, J. Oper. Res. Soc..

[13]  Ching-Ren Chiu,et al.  Decomposition of the environmental inefficiency of the meta-frontier with undesirable output , 2012 .

[14]  Kaoru Tone,et al.  A slacks-based measure of super-efficiency in data envelopment analysis , 2001, Eur. J. Oper. Res..

[15]  Ning Zhang,et al.  Environmental efficiency analysis of transportation system in China:A non-radial DEA approach , 2013 .

[16]  Rolf Färe,et al.  Environmental regulation and profitability: An application to Swedish pulp and paper mills , 1995 .

[17]  Faxin Cheng,et al.  The comparison analysis of total factor productivity and eco-efficiency in China's cement manufactures , 2015 .

[18]  Jin-Li Hu,et al.  Total-factor energy efficiency of regions in Japan , 2008 .

[19]  Zhaohua Wang,et al.  An empirical analysis of China's energy efficiency from both static and dynamic perspectives , 2014 .

[20]  Jin-Li Hu,et al.  Ecological total-factor energy efficiency of regions in China , 2012 .

[21]  Yue-Jun Zhang,et al.  The CO2 emission efficiency, reduction potential and spatial clustering in China's industry: evidence from the regional level , 2016 .

[22]  Hui Wang,et al.  Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach , 2012, Eur. J. Oper. Res..

[23]  Boqiang Lin,et al.  Metafroniter energy efficiency with CO2 emissions and its convergence analysis for China , 2015 .

[24]  Bangzhu Zhu,et al.  Measuring the Interprovincial CO 2 Emissions Considering Electric Power Dispatching in China: From Production and Consumption Perspectives , 2016 .

[25]  Wei Zhang,et al.  China's regional energy and environmental efficiency: A DEA window analysis based dynamic evaluation , 2013, Math. Comput. Model..

[26]  G. Battese,et al.  Metafrontier frameworks for the study of firm-level efficiencies and technology ratios , 2008 .

[27]  Behrouz Arabi,et al.  Power Industry Restructuring and Eco-Efficiency Changes: A New Slacks-Based Model in Malmquist- Luenberger Index Measurement , 2014 .

[28]  Bai-Chen Xie,et al.  Dynamic environmental efficiency evaluation of electric power industries: Evidence from OECD (Organization for Economic Cooperation and Development) and BRIC (Brazil, Russia, India and China) countries , 2014 .

[29]  L. Liang,et al.  Does environmental regulation affect energy efficiency in China's thermal power generation? Empirical evidence from a slacks-based DEA model , 2014 .

[30]  Qunwei Wang,et al.  Energy efficiency and production technology heterogeneity in China: A meta-frontier DEA approach , 2013 .